How we change what others think, feel, believe and do

Inductive Reasoning

Disciplines > Argument > Types of Reasoning > Inductive Reasoning

Description | Example | Discussion | See also

Description

Inductive reasoning, or induction, is reasoning from a specific case or cases and deriving a general rule. It draws inferences from observations in order to make generalizations. In doing so, it recognizes that conclusions may not be certain.

Inference can be done in four stages:

1. Observation: collect facts, without bias.
2. Analysis: classify the facts, identifying patterns of regularity.
3. Inference: From the patterns, infer generalizations about the relations between the facts.
4. Confirmation: Testing the inference through further observation.

In an argument, you might:

• Derive a general rule in an accepted area and then apply the rule in the area where you want the person to behave.
• Give them lots of detail, then explain what it all means.
• Talk about the benefits of the parts and only get to the overall benefits later.
• Take what has happened and give a plausible explanation for why it has happened.

Inductive arguments can include:

• Part-to-whole: where the whole is assumed to be like individual parts (only bigger).
• Extrapolations: where areas beyond the area of study are assumed to be like the studied area.
• Predictions: where the future is assumed to be like the past.

Example

Discussion

Early proponents of induction, such as Francis Bacon, saw it as a way of understanding nature in an unbiased way, as it derives laws from neutral observation.

Induction uses evidence more than logic when it says 'all these are true, so that should be true too'. This can result in a more uncertain and probabilistic conclusion than the more contained and certain deductive reasoning. Inductive arguments are hence always open to question as, by definition, the conclusion is a bigger bag than the evidence on which it is based. This breadth allows it to be used where deductive methods may not work, for example in prediction or invention.

In argument, starting with the detail anchors your persuasion in reality, using immediate sensory data of what can be seen and touched and then going to the big picture of ideas, principles and general rules.

Starting from the small and building up to the big can be less threatening than starting with the big stuff, which can make inductive arguments more persuasive as people may understand the process better than a more clinical deduction.

Scientists create scientific laws by observing a number of phenomena, finding similarities and deriving a law which explains all things. A good scientific law is highly generalized and may be applied in many situations to explain other phenomena. For example the law of gravity was used to predict the movement of the planets. Of course when you find a law, you have to spend ages proving it and convincing others that it is true.

In set theory, an inductively created rule is a superset of the members that are taken as the start point. The only way to prove the rule is to identify all members of the set. This is often impractical. It may, however, be possible to calculate the probability that the rule is true.

In this way, inductive arguments can be made to be more valid and probable by adding evidence, although if this evidence is selectively chosen, it may falsely hide contrary evidence. Inductive reasoning thus needs trust and demonstration of integrity more than deductive reasoning. The clear danger with induction is that it is used to create 'proof' to support beliefs rather than possibilities that facilitate exploration.

Inductive reasoning is also called Generalizing as it takes specific instances and creates a general rule.

See also

Inductive Fallacies, Deductive reasoning, Effects-to-cause reasoning, Chunking questions